Optimal bidding strategy for virtual power plant utilizing multi-stage stochastic dynamic programming

Abstract

Virtual power plants(VPPs) are being deployed owing to the increase of reliance on distributed energy resources (DERs) as well as the development in the energy storage system (ESS). In this study, we propose an optimal bidding strategy model for VPPs in a day-ahead electricity market. This strategic bidding model aims to maximize the expected profit of VPP, taking into account the uncertainties in demand and DER generation. By generating the scenario tree of forecast error, we quantify the uncertain factors. Finally, the problem is modeled as the multi-stage stochastic dynamic program where the bidding decision is made in the first stage and the operation of ESS in the remaining stages. The effectiveness of the proposed strategy has been assessed on a real case study.1